The Lobo Lab

Systems Biology of Growth & Form

At the Lobo Lab we reverse engineer the mechanisms regulating biological growth and form with an integrated systems approach. We focus on understanding, controlling, and designing the dynamic regulation and signaling that control how organisms grow, metabolize their components, and coordinate the formation of patterns and shapes. We closely integrate new computational methods, mathematical models, and bioinformatics approaches with molecular assays at the bench. We seek a mechanistic understanding of development and regeneration, find therapies for cancer and other diseases, and streamline the application of systems and synthetic biology.

News

- New paper presenting a high-performance methodology based on GPU computing for the inference of spatial gene regulatory networks published in Briefings in Bioinformatics.

- Jason presents a poster at the 37th Annual GABS Symposium.

- Alexander Maltsev joins the lab as a graduate research assistant. Welcome Alex!

- Gaby Del Cid joins the lab as a graduate research assistant. Welcome Gaby!


Planarian worms simulation

Systems Biology

We build quantitative mathematical models to understand, analyze, and predict the behavior of biological systems.

Computational AI methods

Computational Methods

We develop computational methods to simulate and infer dynamic models, discover novel elements, and find the best next experiments to test.

Planform

Ontologies and Databases

We create ontologies, curate databases, and develop expert systems used by both human scientists and artificial intelligence machines.

Planarian regeneration

Development and Regeneration

We study how shapes and patterns are formed from a single cell during development and restored through regeneration.

Cancer phenotypes

Cancer and other Diseases

We seek to understand why and how regulatory mechanisms go awry to produce cancer and other diseases.

Knockout metabolic network

Synthetic Biology

We design and optimize regulatory and metabolic networks with desired dynamics and behaviors to solve specific bioengineering problems.